Deep Learning with PyTorch

6 Using a neural network to fit the data

This chapter covers

• Nonlinear activation functions as the key difference compared with linear models
• Working with PyTorch’s nn module
• Solving a linear-fit problem with a neural network

So far, we’ve taken a close look at how a linear model can learn and how to make that happen in PyTorch. We’ve focused on a very simple regression problem that used a linear model with only one input and one output. Such a simple example allowed us to dissect the mechanics of a model that learns, without getting overly distracted by the implementation of the model itself. As we saw in the overview diagram in chapter 5, figure 5.2 (repeated here as figure 6.1), the exact details of a model are not needed to understand ...